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POET: Open-ended Reinforcement Learning Through Unbounded Invention Of Learning Challenges And Their Solutions.pdf

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Preview of POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
🔗 Source: proceedings.mlr.press
📊 Size: 1.29 MB
📄 Pages: 12 pages
⬇️ Downloads: 156

Summary

The Paired Open-Ended Trailblazer (POET) algorithm generates and solves its own challenges, allowing solutions to goal-switch between challenges to avoid local optima. However, the original POET had limitations, including a limited problem space and lack of a universal progress measure. To address these issues, two algorithmic innovations were introduced: (1) a domain-general measure of novelty, enabling the system to create and solve interesting challenges endlessly, and (2) an efficient heuristic for determining when agents should goal-switch. Additionally, two external innovations were introduced: (3) a novel way to encode environmental challenges, and (4) a generic measure of open-ended innovation. The enhanced POET algorithm produces a diverse range of sophisticated behaviors that solve a wide range of environmental challenges, many of which cannot be solved through other means.

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Description

The Paired Open-Ended Trailblazer (POET) algorithm generates and solves its own challenges, allowing solutions to goal-switch between challenges to avoid local...

Technical Information

  • File Format: PDF
  • File Size: 1.29 MB
  • Pages: 12
  • Language: EN
  • Total Downloads: 156
  • Last Updated: 2 weeks ago

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